Gene expression provides a snapshot of the cellular changes that promote tumor malignancy. Quantitative gene expression analysis, especially as implemented by DNA microarrays, has proven to be an extremely valuable tool for cancer genome characterization, and has lead to the development of new genomic-based clinical tests. Our own experience with DNA microarrays to study gene expression patterns for breast, head &neck, and lung cancers has lead to the identification of novel subtypes of tumors with distinct patient outcomes and has identified new tumor suppressor genes. In the pilot phase of The Cancer Genome Atlas (TCGA) project, multiple platforms were used including tools to study gene expression (our role), tumor genomic DNA copy number alterations, SNP genotypes, DNA methylation and gene mutational analyses. Our collaborative efforts identified new tumor subtypes of glioblastoma and painted an integrated picture linking mutations to copy number changes to expression patterns, which identified biologically distinct subtypes of disease with differences in patient outcomes. For the second phase of TCGA project, we propose to continue to perform quantitative gene expression profiling of all protein-coding genes, non-protein coding mRNAs(ncRNAs) and microRNAs, on -2000 tumors per year. This approach has proven to be one of the most informative and comprehensive cancer genome characterization tools available. In addition, we propose to generate global chromatin organization profiles of cancer to identify regions of """"""""open"""""""" chromatin domains (nucleosome-depleted regions). We will use FAIRE (Formaldehyde-Assisted isolation of Regulatory Elements), a simple, low-cost method amenable to use on small quantities of solid tissue, coupled to next-generation DNA sequencing. Since the function of most histone modifications and chromatin remodeling activities is to regulate nucleosome occupancy, FAIRE effectively summarizes the functional output of such epigenetic mechanisms in a single robust assay. Lastly, we propose to perform integrated analyses of transcript levels with chromatin stoicture to map important regulatory elements, which can be distant to the transcript(s) that they regulate. Our study of genome-wide transcript regulation with chromatin organization will provide a critical portrait of the cancer genome that can be integrated with (and indeed can sometimes generate) other important data, including mutations and copy number events.

Public Health Relevance

Cancer is a disease caused by changes in many different genes, and these genes can be altered (or mutated) in many different ways. One way in which alterations can cause cancer is to turn particular genes on, or turn others off. We propose to comprehensively study all human genes and determine their expression levels in cancer and normal tissues, and thus, identify those genes that are inappropriately on or off in the tumors. In addition, we will also study important structural characteristics of person's tumor DNA, and combine these data with our expression measurement in order to provide an improved mechanistic understanding of why certain cancer causing genes are inappropriately expressed.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Resource-Related Research Projects--Cooperative Agreements (U24)
Project #
3U24CA143848-05S1
Application #
8925212
Study Section
Special Emphasis Panel (ZCA1-SRLB-U (O1))
Program Officer
Tarnuzzer, Roy W
Project Start
2009-09-29
Project End
2015-07-31
Budget Start
2014-08-01
Budget End
2015-07-31
Support Year
5
Fiscal Year
2014
Total Cost
$500,000
Indirect Cost
$169,976
Name
University of North Carolina Chapel Hill
Department
Genetics
Type
Schools of Medicine
DUNS #
608195277
City
Chapel Hill
State
NC
Country
United States
Zip Code
27599
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Fishbein, Lauren; Leshchiner, Ignaty; Walter, Vonn et al. (2017) Comprehensive Molecular Characterization of Pheochromocytoma and Paraganglioma. Cancer Cell 31:181-193
Cancer Genome Atlas Research Network; Analysis Working Group: Asan University; BC Cancer Agency et al. (2017) Integrated genomic characterization of oesophageal carcinoma. Nature 541:169-175
Huo, Dezheng; Hu, Hai; Rhie, Suhn K et al. (2017) Comparison of Breast Cancer Molecular Features and Survival by African and European Ancestry in The Cancer Genome Atlas. JAMA Oncol 3:1654-1662
Kimes, Patrick K; Liu, Yufeng; Neil Hayes, David et al. (2017) Statistical significance for hierarchical clustering. Biometrics 73:811-821
Robertson, A Gordon; Shih, Juliann; Yau, Christina et al. (2017) Integrative Analysis Identifies Four Molecular and Clinical Subsets in Uveal Melanoma. Cancer Cell 32:204-220.e15
Cancer Genome Atlas Research Network. Electronic address: wheeler@bcm.edu; Cancer Genome Atlas Research Network (2017) Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma. Cell 169:1327-1341.e23

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